China's commitment to peak carbon dioxide emissions before 2030 and achieve carbon neutrality by 2060 necessitates effective policy instruments. Green credit, recognized as a crucial tool for sustainable development, plays a vital role in optimizing resource allocation, mitigating environmental risks, and guiding corporate behavior. This study focuses on the impact of the 2012 Green Credit Guidelines, a pivotal moment in China's green credit policy development, on corporate ESG performance. While China has seen a substantial increase in green credit, a rigorous assessment is needed to determine the policy's effectiveness in incentivizing environmentally and socially responsible corporate behavior. ESG evaluation indicators, encompassing environmental, social, and governance dimensions, serve as essential benchmarks for evaluating this performance. Previous research has indirectly assessed the policy's impact through factors like green innovation, environmental investments, and environmental governance, but direct research on the relationship between green credit policy and corporate ESG performance remains limited. This study addresses this gap by examining the policy's effects, considering both the 'traditional finance attribute' and 'environmental regulation attribute' of green credit, and exploring the role of green innovation in mediating the policy's impact. The study aims to provide a comprehensive theoretical and empirical analysis of the policy's influence on corporate ESG performance.

Existing literature examines the dual aspects of guidance and restriction inherent in green credit policy, exploring its environmental and social consequences through its traditional finance and environmental regulation attributes. The traditional finance attribute highlights the influence on external financing conditions of polluting enterprises, leading to either a 'forcing effect' (compelling environmental initiatives) or a 'crowding out effect' (diverting investments from environmental projects). The environmental regulation attribute emphasizes the policy's guiding function, stimulating environmental projects through an 'incentive effect'. However, the literature often overlooks the potential exacerbation of financing conditions and the crowding-out effect, and the crucial mechanism of green innovation. This study builds upon this existing literature by directly investigating the relationship between green credit policy and corporate ESG performance, and exploring the mediating role of green innovation.

This study employs a quasi-natural experiment framework using a difference-in-differences (DID) model. The sample includes A-share listed companies in China from 2009 to 2019, categorized into a treatment group (16 heavily polluting industries) and a control group (non-polluting industries). The 2012 introduction of the Green Credit Guidelines serves as the policy intervention. The dependent variable is the annual ESG score from Huazheng, a comprehensive ESG rating agency. The core explanatory variable is the interaction term of the treatment group and the post-policy period. Control variables include firm characteristics (age, asset-liability ratio, total assets, etc.), and fixed effects (firm, year, and province) are included to account for unobservable factors. Parallel trend tests are conducted to verify the assumption of pre-existing trends. Robustness tests are performed by replacing the dependent variable, changing the data source, excluding exogenous policy interference, and using the propensity score matching-difference-in-differences (PSM-DID) method. Placebo tests (counterfactual and random drawing) are conducted to ensure the validity of results. A moderating effect model examines the crowding out effect, using the SA and WW indices as measures of external financing constraints. Finally, a mediation model analyzes the green innovation channel using different types of green patents (total patents, invention patents, utility model patents) as mediators to explore the relationship between green credit policy and ESG performance. Heterogeneity analysis examines differences based on ownership structure (State-owned vs. Non-state-owned) and firm size.

The baseline regression results show a significantly negative coefficient for the interaction term (policy implementation and polluting industries), indicating that the green credit policy led to a decrease in ESG scores of polluting enterprises. This result is robust across various robustness tests, including those involving different dependent variables, data sources, regression methods (PSM-DID), and exclusion of exogenous policy influence. Placebo tests further support this finding. The crowding-out effect analysis confirms that increased external financing constraints exacerbate the negative impact of the policy on ESG performance. The analysis of the green innovation channel reveals a significant negative impact of the policy on green innovation (both quality and quantity), contributing to the decline in ESG performance. Heterogeneity analysis shows that the negative impact is more pronounced for non-state-owned enterprises, supporting the hypothesis of credit discrimination. However, no significant difference is found based on enterprise size.

The findings challenge the assumption that green credit policies automatically lead to improved ESG performance. The study highlights the importance of considering the potential negative consequences of such policies, especially the crowding-out effect and potential for credit discrimination. The negative impact on green innovation suggests that simply restricting access to credit for polluting firms is insufficient. A more nuanced approach is required, which considers the potential for unintended consequences and the need to actively promote green innovation. The results highlight the need for policy design that promotes both environmental protection and economic development, rather than simply imposing restrictions.

This study contributes to the understanding of green credit policy effectiveness by demonstrating its negative impact on ESG performance of polluting enterprises in China. The crowding-out effect and the negative influence on green innovation are key factors. Future research could explore alternative policy mechanisms that effectively stimulate green innovation without crowding out essential resources or exacerbating inequalities. More detailed investigations into the heterogeneity of impacts based on firm characteristics are also warranted.

The study relies on publicly available ESG data, which might not fully capture the complexities of corporate ESG performance. The focus is on China, limiting generalizability to other contexts. The study only covers the period until 2019, not incorporating recent policy developments or the long-term effects of the Green Credit Guidelines.